Pandas Profiling Report

Dataset statistics

Number of variables	17
Number of observations	1000
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	132.9 KiB
Average record size in memory	136.1 B

Variable types

Categorical	9
Numeric	7
DateTime	1

Alerts

`Porcentagem margem bruta` has constant value "4.761904762"	Constant
`ID_fatura` has a high cardinality: 1000 distinct values	High cardinality
`Horario` has a high cardinality: 506 distinct values	High cardinality
`Preco unitario` is highly correlated with `Imposto` and 3 other fields	High correlation
`Quantidade` is highly correlated with `Imposto` and 3 other fields	High correlation
`Imposto` is highly correlated with `Preco unitario` and 4 other fields	High correlation
`Total` is highly correlated with `Preco unitario` and 4 other fields	High correlation
`Custo mercadoria` is highly correlated with `Preco unitario` and 4 other fields	High correlation
`Renda bruta` is highly correlated with `Preco unitario` and 4 other fields	High correlation
`Nota da experiência de compra` is highly correlated with `Porcentagem margem bruta`	High correlation
`Filial` is highly correlated with `Cidade`	High correlation
`Cidade` is highly correlated with `Filial`	High correlation
`Tipo de cliente` is highly correlated with `Porcentagem margem bruta`	High correlation
`Sexo` is highly correlated with `Porcentagem margem bruta`	High correlation
`Linha de produtos` is highly correlated with `Porcentagem margem bruta`	High correlation
`Pagamento` is highly correlated with `Porcentagem margem bruta`	High correlation
`Porcentagem margem bruta` is highly correlated with `Cidade` and 5 other fields	High correlation
`ID_fatura` is uniformly distributed	Uniform
`Horario` is uniformly distributed	Uniform
`ID_fatura` has unique values	Unique

Reproduction

Analysis started	2023-06-27 11:27:44.567770
Analysis finished	2023-06-27 11:28:11.038819
Duration	26.47 seconds
Software version	pandas-profiling v3.4.0
Download configuration	config.json

ID_fatura
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

750-67-8428	1
642-61-4706	1
816-72-8853	1
491-38-3499	1
322-02-2271	1
Other values (995)	995

Length

Max length	11
Median length	11
Mean length	11
Min length	11

Characters and Unicode

Total characters	11000
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1000 ?
Unique (%)	100.0%

Sample

1st row	750-67-8428
2nd row	226-31-3081
3rd row	631-41-3108
4th row	123-19-1176
5th row	373-73-7910

Common Values

Value	Count	Frequency (%)
750-67-8428	1	0.1%
642-61-4706	1	0.1%
816-72-8853	1	0.1%
491-38-3499	1	0.1%
322-02-2271	1	0.1%
842-29-4695	1	0.1%
725-67-2480	1	0.1%
641-51-2661	1	0.1%
714-02-3114	1	0.1%
518-17-2983	1	0.1%
Other values (990)	990	99.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
750-67-8428	1	0.1%
252-56-2699	1	0.1%
871-79-8483	1	0.1%
848-62-7243	1	0.1%
631-41-3108	1	0.1%
123-19-1176	1	0.1%
373-73-7910	1	0.1%
699-14-3026	1	0.1%
355-53-5943	1	0.1%
315-22-5665	1	0.1%
Other values (990)	990	99.0%

Most occurring characters

Value	Count	Frequency (%)
-	2000	18.2%
2	957	8.7%
6	954	8.7%
1	950	8.6%
8	944	8.6%
5	927	8.4%
4	918	8.3%
3	909	8.3%
7	895	8.1%
0	809	7.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	9000	81.8%
Dash Punctuation	2000	18.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	957	10.6%
6	954	10.6%
1	950	10.6%
8	944	10.5%
5	927	10.3%
4	918	10.2%
3	909	10.1%
7	895	9.9%
0	809	9.0%
9	737	8.2%

Dash Punctuation

Value	Count	Frequency (%)
-	2000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
-	2000	18.2%
2	957	8.7%
6	954	8.7%
1	950	8.6%
8	944	8.6%
5	927	8.4%
4	918	8.3%
3	909	8.3%
7	895	8.1%
0	809	7.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
-	2000	18.2%
2	957	8.7%
6	954	8.7%
1	950	8.6%
8	944	8.6%
5	927	8.4%
4	918	8.3%
3	909	8.3%
7	895	8.1%
0	809	7.4%

Filial
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

A	340
B	332
C	328

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1000
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A
2nd row	C
3rd row	A
4th row	A
5th row	A

Common Values

Value	Count	Frequency (%)
A	340	34.0%
B	332	33.2%
C	328	32.8%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
a	340	34.0%
b	332	33.2%
c	328	32.8%

Most occurring characters

Value	Count	Frequency (%)
A	340	34.0%
B	332	33.2%
C	328	32.8%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1000	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	340	34.0%
B	332	33.2%
C	328	32.8%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1000	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	340	34.0%
B	332	33.2%
C	328	32.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	340	34.0%
B	332	33.2%
C	328	32.8%

Cidade
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Yangon	340
Mandalay	332
Naypyitaw	328

Length

Max length	9
Median length	8
Mean length	7.648
Min length	6

Characters and Unicode

Total characters	7648
Distinct characters	14
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Yangon
2nd row	Naypyitaw
3rd row	Yangon
4th row	Yangon
5th row	Yangon

Common Values

Value	Count	Frequency (%)
Yangon	340	34.0%
Mandalay	332	33.2%
Naypyitaw	328	32.8%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
yangon	340	34.0%
mandalay	332	33.2%
naypyitaw	328	32.8%

Most occurring characters

Value	Count	Frequency (%)
a	1992	26.0%
n	1012	13.2%
y	988	12.9%
Y	340	4.4%
g	340	4.4%
o	340	4.4%
M	332	4.3%
d	332	4.3%
l	332	4.3%
N	328	4.3%
Other values (4)	1312	17.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	6648	86.9%
Uppercase Letter	1000	13.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	1992	30.0%
n	1012	15.2%
y	988	14.9%
g	340	5.1%
o	340	5.1%
d	332	5.0%
l	332	5.0%
p	328	4.9%
i	328	4.9%
t	328	4.9%

Uppercase Letter

Value	Count	Frequency (%)
Y	340	34.0%
M	332	33.2%
N	328	32.8%

Most occurring scripts

Value	Count	Frequency (%)
Latin	7648	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	1992	26.0%
n	1012	13.2%
y	988	12.9%
Y	340	4.4%
g	340	4.4%
o	340	4.4%
M	332	4.3%
d	332	4.3%
l	332	4.3%
N	328	4.3%
Other values (4)	1312	17.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7648	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	1992	26.0%
n	1012	13.2%
y	988	12.9%
Y	340	4.4%
g	340	4.4%
o	340	4.4%
M	332	4.3%
d	332	4.3%
l	332	4.3%
N	328	4.3%
Other values (4)	1312	17.2%

Tipo de cliente
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Member	501
Normal	499

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	6000
Distinct characters	9
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Member
2nd row	Normal
3rd row	Normal
4th row	Member
5th row	Normal

Common Values

Value	Count	Frequency (%)
Member	501	50.1%
Normal	499	49.9%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
member	501	50.1%
normal	499	49.9%

Most occurring characters

Value	Count	Frequency (%)
e	1002	16.7%
m	1000	16.7%
r	1000	16.7%
M	501	8.3%
b	501	8.3%
N	499	8.3%
o	499	8.3%
a	499	8.3%
l	499	8.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5000	83.3%
Uppercase Letter	1000	16.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	1002	20.0%
m	1000	20.0%
r	1000	20.0%
b	501	10.0%
o	499	10.0%
a	499	10.0%
l	499	10.0%

Uppercase Letter

Value	Count	Frequency (%)
M	501	50.1%
N	499	49.9%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6000	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	1002	16.7%
m	1000	16.7%
r	1000	16.7%
M	501	8.3%
b	501	8.3%
N	499	8.3%
o	499	8.3%
a	499	8.3%
l	499	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	1002	16.7%
m	1000	16.7%
r	1000	16.7%
M	501	8.3%
b	501	8.3%
N	499	8.3%
o	499	8.3%
a	499	8.3%
l	499	8.3%

Sexo
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Female	501
Male	499

Length

Max length	6
Median length	6
Mean length	5.002
Min length	4

Characters and Unicode

Total characters	5002
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Female
2nd row	Female
3rd row	Male
4th row	Male
5th row	Male

Common Values

Value	Count	Frequency (%)
Female	501	50.1%
Male	499	49.9%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
female	501	50.1%
male	499	49.9%

Most occurring characters

Value	Count	Frequency (%)
e	1501	30.0%
a	1000	20.0%
l	1000	20.0%
F	501	10.0%
m	501	10.0%
M	499	10.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4002	80.0%
Uppercase Letter	1000	20.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	1501	37.5%
a	1000	25.0%
l	1000	25.0%
m	501	12.5%

Uppercase Letter

Value	Count	Frequency (%)
F	501	50.1%
M	499	49.9%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5002	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	1501	30.0%
a	1000	20.0%
l	1000	20.0%
F	501	10.0%
m	501	10.0%
M	499	10.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5002	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	1501	30.0%
a	1000	20.0%
l	1000	20.0%
F	501	10.0%
m	501	10.0%
M	499	10.0%

Linha de produtos
Categorical

HIGH CORRELATION

Distinct	6
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Fashion accessories	178
Food and beverages	174
Electronic accessories	170
Sports and travel	166
Home and lifestyle	160

Length

Max length	22
Median length	19
Mean length	18.54
Min length	17

Characters and Unicode

Total characters	18540
Distinct characters	25
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Health and beauty
2nd row	Electronic accessories
3rd row	Home and lifestyle
4th row	Health and beauty
5th row	Sports and travel

Common Values

Value	Count	Frequency (%)
Fashion accessories	178	17.8%
Food and beverages	174	17.4%
Electronic accessories	170	17.0%
Sports and travel	166	16.6%
Home and lifestyle	160	16.0%
Health and beauty	152	15.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
and	652	24.6%
accessories	348	13.1%
fashion	178	6.7%
food	174	6.6%
beverages	174	6.6%
electronic	170	6.4%
sports	166	6.3%
travel	166	6.3%
home	160	6.0%
lifestyle	160	6.0%
Other values (2)	304	11.5%

Most occurring characters

Value	Count	Frequency (%)
e	2338	12.6%
a	1822	9.8%
s	1722	9.3%
	1652	8.9%
o	1370	7.4%
c	1036	5.6%
r	1024	5.5%
n	1000	5.4%
t	966	5.2%
i	856	4.6%
Other values (15)	4754	25.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	15888	85.7%
Space Separator	1652	8.9%
Uppercase Letter	1000	5.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	2338	14.7%
a	1822	11.5%
s	1722	10.8%
o	1370	8.6%
c	1036	6.5%
r	1024	6.4%
n	1000	6.3%
t	966	6.1%
i	856	5.4%
d	826	5.2%
Other values (10)	2928	18.4%

Uppercase Letter

Value	Count	Frequency (%)
F	352	35.2%
H	312	31.2%
E	170	17.0%
S	166	16.6%

Space Separator

Value	Count	Frequency (%)
	1652	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	16888	91.1%
Common	1652	8.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	2338	13.8%
a	1822	10.8%
s	1722	10.2%
o	1370	8.1%
c	1036	6.1%
r	1024	6.1%
n	1000	5.9%
t	966	5.7%
i	856	5.1%
d	826	4.9%
Other values (14)	3928	23.3%

Common

Value	Count	Frequency (%)
	1652	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	18540	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	2338	12.6%
a	1822	9.8%
s	1722	9.3%
	1652	8.9%
o	1370	7.4%
c	1036	5.6%
r	1024	5.5%
n	1000	5.4%
t	966	5.2%
i	856	4.6%
Other values (15)	4754	25.6%

Preco unitario
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	943
Distinct (%)	94.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	55.67213

Minimum	10.08
Maximum	99.96
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	10.08
5-th percentile	15.279
Q1	32.875
median	55.23
Q3	77.935
95-th percentile	97.222
Maximum	99.96
Range	89.88
Interquartile range (IQR)	45.06

Descriptive statistics

Standard deviation	26.49462835
Coefficient of variation (CV)	0.4759047004
Kurtosis	-1.218591428
Mean	55.67213
Median Absolute Deviation (MAD)	22.505
Skewness	0.007077447853
Sum	55672.13
Variance	701.9653313
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
83.77	3	0.3%
39.62	2	0.2%
24.74	2	0.2%
19.15	2	0.2%
73.47	2	0.2%
95.54	2	0.2%
78.31	2	0.2%
26.26	2	0.2%
89.48	2	0.2%
72.88	2	0.2%
Other values (933)	979	97.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
10.08	1	0.1%
10.13	1	0.1%
10.16	1	0.1%
10.17	1	0.1%
10.18	1	0.1%
10.53	1	0.1%
10.56	1	0.1%
10.59	1	0.1%
10.69	1	0.1%
10.75	1	0.1%

Value	Count	Frequency (%)
99.96	2	0.2%
99.92	1	0.1%
99.89	1	0.1%
99.83	1	0.1%
99.82	2	0.2%
99.79	1	0.1%
99.78	1	0.1%
99.73	1	0.1%
99.71	1	0.1%
99.7	1	0.1%

Quantidade
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	10
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.51

Minimum	1
Maximum	10
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	3
median	5
Q3	8
95-th percentile	10
Maximum	10
Range	9
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	2.923430595
Coefficient of variation (CV)	0.5305681661
Kurtosis	-1.215547226
Mean	5.51
Median Absolute Deviation (MAD)	2
Skewness	0.01294104802
Sum	5510
Variance	8.546446446
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
10	119	11.9%
1	112	11.2%
4	109	10.9%
7	102	10.2%
5	102	10.2%
6	98	9.8%
9	92	9.2%
2	91	9.1%
3	90	9.0%
8	85	8.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	112	11.2%
2	91	9.1%
3	90	9.0%
4	109	10.9%
5	102	10.2%
6	98	9.8%
7	102	10.2%
8	85	8.5%
9	92	9.2%
10	119	11.9%

Value	Count	Frequency (%)
10	119	11.9%
9	92	9.2%
8	85	8.5%
7	102	10.2%
6	98	9.8%
5	102	10.2%
4	109	10.9%
3	90	9.0%
2	91	9.1%
1	112	11.2%

Imposto
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	990
Distinct (%)	99.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	15.379369

Minimum	0.5085
Maximum	49.65
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	0.5085
5-th percentile	1.955725
Q1	5.924875
median	12.088
Q3	22.44525
95-th percentile	39.1665
Maximum	49.65
Range	49.1415
Interquartile range (IQR)	16.520375

Descriptive statistics

Standard deviation	11.70882548
Coefficient of variation (CV)	0.7613332823
Kurtosis	-0.0818847579
Mean	15.379369
Median Absolute Deviation (MAD)	7.50875
Skewness	0.892569805
Sum	15379.369
Variance	137.0965941
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10.326	2	0.2%
4.464	2	0.2%
4.154	2	0.2%
9.0045	2	0.2%
22.428	2	0.2%
39.48	2	0.2%
10.3635	2	0.2%
8.377	2	0.2%
13.188	2	0.2%
12.57	2	0.2%
Other values (980)	980	98.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.5085	1	0.1%
0.6045	1	0.1%
0.627	1	0.1%
0.639	1	0.1%
0.699	1	0.1%
0.767	1	0.1%
0.7715	1	0.1%
0.775	1	0.1%
0.814	1	0.1%
0.8875	1	0.1%

Value	Count	Frequency (%)
49.65	1	0.1%
49.49	1	0.1%
49.26	1	0.1%
48.75	1	0.1%
48.69	1	0.1%
48.685	1	0.1%
48.605	1	0.1%
47.79	1	0.1%
47.72	1	0.1%
45.325	1	0.1%

Total
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	990
Distinct (%)	99.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	322.96682

Minimum	10.68
Maximum	1042.65
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	10.68
5-th percentile	41.074
Q1	124.425
median	253.85
Q3	471.35
95-th percentile	822.501
Maximum	1042.65
Range	1031.97
Interquartile range (IQR)	346.925

Descriptive statistics

Standard deviation	245.8853975
Coefficient of variation (CV)	0.7613333083
Kurtosis	-0.08188596017
Mean	322.96682
Median Absolute Deviation (MAD)	157.685
Skewness	0.8925696949
Sum	322966.82
Variance	60459.62872
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
216.85	2	0.2%
93.74	2	0.2%
87.23	2	0.2%
189.09	2	0.2%
470.99	2	0.2%
829.08	2	0.2%
217.63	2	0.2%
175.92	2	0.2%
276.95	2	0.2%
263.97	2	0.2%
Other values (980)	980	98.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
10.68	1	0.1%
12.69	1	0.1%
13.17	1	0.1%
13.42	1	0.1%
14.68	1	0.1%
16.11	1	0.1%
16.2	1	0.1%
16.27	1	0.1%
17.09	1	0.1%
18.64	1	0.1%

Value	Count	Frequency (%)
1042.65	1	0.1%
1039.29	1	0.1%
1034.46	1	0.1%
1023.75	1	0.1%
1022.49	1	0.1%
1022.38	1	0.1%
1020.7	1	0.1%
1003.59	1	0.1%
1002.12	1	0.1%
951.82	1	0.1%

Data
Date

Distinct	89
Distinct (%)	8.9%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Minimum	2019-01-01 00:00:00
Maximum	2019-03-30 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

Horario
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	506
Distinct (%)	50.6%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

19:48	7
14:42	7
17:38	6
17:16	5
11:40	5
Other values (501)	970

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	5000
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	210 ?
Unique (%)	21.0%

Sample

1st row	13:08
2nd row	10:29
3rd row	13:23
4th row	20:33
5th row	10:37

Common Values

Value	Count	Frequency (%)
19:48	7	0.7%
14:42	7	0.7%
17:38	6	0.6%
17:16	5	0.5%
11:40	5	0.5%
13:48	5	0.5%
19:39	5	0.5%
19:20	5	0.5%
17:36	5	0.5%
13:58	5	0.5%
Other values (496)	945	94.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
19:48	7	0.7%
14:42	7	0.7%
17:38	6	0.6%
17:36	5	0.5%
19:44	5	0.5%
11:51	5	0.5%
10:11	5	0.5%
13:58	5	0.5%
19:30	5	0.5%
19:20	5	0.5%
Other values (496)	945	94.5%

Most occurring characters

Value	Count	Frequency (%)
1	1250	25.0%
:	1000	20.0%
2	441	8.8%
0	437	8.7%
3	378	7.6%
4	376	7.5%
5	354	7.1%
8	216	4.3%
9	200	4.0%
6	184	3.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4000	80.0%
Other Punctuation	1000	20.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	1250	31.2%
2	441	11.0%
0	437	10.9%
3	378	9.4%
4	376	9.4%
5	354	8.8%
8	216	5.4%
9	200	5.0%
6	184	4.6%
7	164	4.1%

Other Punctuation

Value	Count	Frequency (%)
:	1000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	5000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	1250	25.0%
:	1000	20.0%
2	441	8.8%
0	437	8.7%
3	378	7.6%
4	376	7.5%
5	354	7.1%
8	216	4.3%
9	200	4.0%
6	184	3.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	1250	25.0%
:	1000	20.0%
2	441	8.8%
0	437	8.7%
3	378	7.6%
4	376	7.5%
5	354	7.1%
8	216	4.3%
9	200	4.0%
6	184	3.7%

Pagamento
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Ewallet	345
Cash	344
Credit card	311

Length

Max length	11
Median length	7
Mean length	7.212
Min length	4

Characters and Unicode

Total characters	7212
Distinct characters	14
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Ewallet
2nd row	Cash
3rd row	Credit card
4th row	Ewallet
5th row	Ewallet

Common Values

Value	Count	Frequency (%)
Ewallet	345	34.5%
Cash	344	34.4%
Credit card	311	31.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
ewallet	345	26.3%
cash	344	26.2%
credit	311	23.7%
card	311	23.7%

Most occurring characters

Value	Count	Frequency (%)
a	1000	13.9%
l	690	9.6%
e	656	9.1%
t	656	9.1%
C	655	9.1%
r	622	8.6%
d	622	8.6%
E	345	4.8%
w	345	4.8%
s	344	4.8%
Other values (4)	1277	17.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5901	81.8%
Uppercase Letter	1000	13.9%
Space Separator	311	4.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	1000	16.9%
l	690	11.7%
e	656	11.1%
t	656	11.1%
r	622	10.5%
d	622	10.5%
w	345	5.8%
s	344	5.8%
h	344	5.8%
i	311	5.3%

Uppercase Letter

Value	Count	Frequency (%)
C	655	65.5%
E	345	34.5%

Space Separator

Value	Count	Frequency (%)
	311	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6901	95.7%
Common	311	4.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	1000	14.5%
l	690	10.0%
e	656	9.5%
t	656	9.5%
C	655	9.5%
r	622	9.0%
d	622	9.0%
E	345	5.0%
w	345	5.0%
s	344	5.0%
Other values (3)	966	14.0%

Common

Value	Count	Frequency (%)
	311	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7212	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	1000	13.9%
l	690	9.6%
e	656	9.1%
t	656	9.1%
C	655	9.1%
r	622	8.6%
d	622	8.6%
E	345	4.8%
w	345	4.8%
s	344	4.8%
Other values (4)	1277	17.7%

Custo mercadoria
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	990
Distinct (%)	99.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	307.58738

Minimum	10.17
Maximum	993
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	10.17
5-th percentile	39.1145
Q1	118.4975
median	241.76
Q3	448.905
95-th percentile	783.33
Maximum	993
Range	982.83
Interquartile range (IQR)	330.4075

Descriptive statistics

Standard deviation	234.1765096
Coefficient of variation (CV)	0.7613332823
Kurtosis	-0.0818847579
Mean	307.58738
Median Absolute Deviation (MAD)	150.175
Skewness	0.892569805
Sum	307587.38
Variance	54838.63766
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
206.52	2	0.2%
89.28	2	0.2%
83.08	2	0.2%
180.09	2	0.2%
448.56	2	0.2%
789.6	2	0.2%
207.27	2	0.2%
167.54	2	0.2%
263.76	2	0.2%
251.4	2	0.2%
Other values (980)	980	98.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
10.17	1	0.1%
12.09	1	0.1%
12.54	1	0.1%
12.78	1	0.1%
13.98	1	0.1%
15.34	1	0.1%
15.43	1	0.1%
15.5	1	0.1%
16.28	1	0.1%
17.75	1	0.1%

Value	Count	Frequency (%)
993	1	0.1%
989.8	1	0.1%
985.2	1	0.1%
975	1	0.1%
973.8	1	0.1%
973.7	1	0.1%
972.1	1	0.1%
955.8	1	0.1%
954.4	1	0.1%
906.5	1	0.1%

Porcentagem margem bruta
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

4.761904762	1000

Length

Max length	11
Median length	11
Mean length	11
Min length	11

Characters and Unicode

Total characters	11000
Distinct characters	8
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	4.761904762
2nd row	4.761904762
3rd row	4.761904762
4th row	4.761904762
5th row	4.761904762

Common Values

Value	Count	Frequency (%)
4.761904762	1000	100.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
4.761904762	1000	100.0%

Most occurring characters

Value	Count	Frequency (%)
4	2000	18.2%
7	2000	18.2%
6	2000	18.2%
.	1000	9.1%
1	1000	9.1%
9	1000	9.1%
0	1000	9.1%
2	1000	9.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10000	90.9%
Other Punctuation	1000	9.1%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
4	2000	20.0%
7	2000	20.0%
6	2000	20.0%
1	1000	10.0%
9	1000	10.0%
0	1000	10.0%
2	1000	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	1000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
4	2000	18.2%
7	2000	18.2%
6	2000	18.2%
.	1000	9.1%
1	1000	9.1%
9	1000	9.1%
0	1000	9.1%
2	1000	9.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
4	2000	18.2%
7	2000	18.2%
6	2000	18.2%
.	1000	9.1%
1	1000	9.1%
9	1000	9.1%
0	1000	9.1%
2	1000	9.1%

Renda bruta
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	990
Distinct (%)	99.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	15.379369

Minimum	0.5085
Maximum	49.65
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	0.5085
5-th percentile	1.955725
Q1	5.924875
median	12.088
Q3	22.44525
95-th percentile	39.1665
Maximum	49.65
Range	49.1415
Interquartile range (IQR)	16.520375

Descriptive statistics

Standard deviation	11.70882548
Coefficient of variation (CV)	0.7613332823
Kurtosis	-0.0818847579
Mean	15.379369
Median Absolute Deviation (MAD)	7.50875
Skewness	0.892569805
Sum	15379.369
Variance	137.0965941
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10.326	2	0.2%
4.464	2	0.2%
4.154	2	0.2%
9.0045	2	0.2%
22.428	2	0.2%
39.48	2	0.2%
10.3635	2	0.2%
8.377	2	0.2%
13.188	2	0.2%
12.57	2	0.2%
Other values (980)	980	98.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.5085	1	0.1%
0.6045	1	0.1%
0.627	1	0.1%
0.639	1	0.1%
0.699	1	0.1%
0.767	1	0.1%
0.7715	1	0.1%
0.775	1	0.1%
0.814	1	0.1%
0.8875	1	0.1%

Value	Count	Frequency (%)
49.65	1	0.1%
49.49	1	0.1%
49.26	1	0.1%
48.75	1	0.1%
48.69	1	0.1%
48.685	1	0.1%
48.605	1	0.1%
47.79	1	0.1%
47.72	1	0.1%
45.325	1	0.1%

Nota da experiência de compra
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	61
Distinct (%)	6.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.9727

Minimum	4
Maximum	10
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	4
5-th percentile	4.295
Q1	5.5
median	7
Q3	8.5
95-th percentile	9.7
Maximum	10
Range	6
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	1.718580294
Coefficient of variation (CV)	0.2464727142
Kurtosis	-1.151586839
Mean	6.9727
Median Absolute Deviation (MAD)	1.5
Skewness	0.009009648766
Sum	6972.7
Variance	2.953518228
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
6	26	2.6%
6.6	24	2.4%
4.2	22	2.2%
9.5	22	2.2%
6.5	21	2.1%
5	21	2.1%
6.2	21	2.1%
8	21	2.1%
5.1	21	2.1%
7.6	20	2.0%
Other values (51)	781	78.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
4	11	1.1%
4.1	17	1.7%
4.2	22	2.2%
4.3	18	1.8%
4.4	17	1.7%
4.5	17	1.7%
4.6	8	0.8%
4.7	12	1.2%
4.8	13	1.3%
4.9	18	1.8%

Value	Count	Frequency (%)
10	5	0.5%
9.9	16	1.6%
9.8	19	1.9%
9.7	14	1.4%
9.6	17	1.7%
9.5	22	2.2%
9.4	12	1.2%
9.3	16	1.6%
9.2	16	1.6%
9.1	14	1.4%

Auto

The auto setting is an easily interpretable pairwise column metric of the following mapping: vartype-vartype : method, categorical-categorical : Cramer's V, numerical-categorical : Cramer's V (using a discretized numerical column), numerical-numerical : Spearman's ρ. This configuration uses the best suitable for each pair of columns.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count

A simple visualization of nullity by column.

First rows

	ID_fatura	Filial	Cidade	Tipo de cliente	Sexo	Linha de produtos	Preco unitario	Quantidade	Imposto	Total	Data	Horario	Pagamento	Custo mercadoria	Porcentagem margem bruta	Renda bruta	Nota da experiência de compra
0	750-67-8428	A	Yangon	Member	Female	Health and beauty	74.69	7	26.1415	548.97	2019-01-05	13:08	Ewallet	522.83	4.761905	26.1415	9.1
1	226-31-3081	C	Naypyitaw	Normal	Female	Electronic accessories	15.28	5	3.8200	80.22	2019-03-08	10:29	Cash	76.40	4.761905	3.8200	9.6
2	631-41-3108	A	Yangon	Normal	Male	Home and lifestyle	46.33	7	16.2155	340.53	2019-03-03	13:23	Credit card	324.31	4.761905	16.2155	7.4
3	123-19-1176	A	Yangon	Member	Male	Health and beauty	58.22	8	23.2880	489.05	2019-01-27	20:33	Ewallet	465.76	4.761905	23.2880	8.4
4	373-73-7910	A	Yangon	Normal	Male	Sports and travel	86.31	7	30.2085	634.38	2019-02-08	10:37	Ewallet	604.17	4.761905	30.2085	5.3
5	699-14-3026	C	Naypyitaw	Normal	Male	Electronic accessories	85.39	7	29.8865	627.62	2019-03-25	18:30	Ewallet	597.73	4.761905	29.8865	4.1
6	355-53-5943	A	Yangon	Member	Female	Electronic accessories	68.84	6	20.6520	433.69	2019-02-25	14:36	Ewallet	413.04	4.761905	20.6520	5.8
7	315-22-5665	C	Naypyitaw	Normal	Female	Home and lifestyle	73.56	10	36.7800	772.38	2019-02-24	11:38	Ewallet	735.60	4.761905	36.7800	8.0
8	665-32-9167	A	Yangon	Member	Female	Health and beauty	36.26	2	3.6260	76.15	2019-01-10	17:15	Credit card	72.52	4.761905	3.6260	7.2
9	692-92-5582	B	Mandalay	Member	Female	Food and beverages	54.84	3	8.2260	172.75	2019-02-20	13:27	Credit card	164.52	4.761905	8.2260	5.9

Last rows

	ID_fatura	Filial	Cidade	Tipo de cliente	Sexo	Linha de produtos	Preco unitario	Quantidade	Imposto	Total	Data	Horario	Pagamento	Custo mercadoria	Porcentagem margem bruta	Renda bruta	Nota da experiência de compra
990	886-18-2897	A	Yangon	Normal	Female	Food and beverages	56.56	5	14.1400	296.94	2019-03-22	19:06	Credit card	282.80	4.761905	14.1400	4.5
991	602-16-6955	B	Mandalay	Normal	Female	Sports and travel	76.60	10	38.3000	804.30	2019-01-24	18:10	Ewallet	766.00	4.761905	38.3000	6.0
992	745-74-0715	A	Yangon	Normal	Male	Electronic accessories	58.03	2	5.8030	121.86	2019-03-10	20:46	Ewallet	116.06	4.761905	5.8030	8.8
993	690-01-6631	B	Mandalay	Normal	Male	Fashion accessories	17.49	10	8.7450	183.64	2019-02-22	18:35	Ewallet	174.90	4.761905	8.7450	6.6
994	652-49-6720	C	Naypyitaw	Member	Female	Electronic accessories	60.95	1	3.0475	64.00	2019-02-18	11:40	Ewallet	60.95	4.761905	3.0475	5.9
995	233-67-5758	C	Naypyitaw	Normal	Male	Health and beauty	40.35	1	2.0175	42.37	2019-01-29	13:46	Ewallet	40.35	4.761905	2.0175	6.2
996	303-96-2227	B	Mandalay	Normal	Female	Home and lifestyle	97.38	10	48.6900	1022.49	2019-03-02	17:16	Ewallet	973.80	4.761905	48.6900	4.4
997	727-02-1313	A	Yangon	Member	Male	Food and beverages	31.84	1	1.5920	33.43	2019-02-09	13:22	Cash	31.84	4.761905	1.5920	7.7
998	347-56-2442	A	Yangon	Normal	Male	Home and lifestyle	65.82	1	3.2910	69.11	2019-02-22	15:33	Cash	65.82	4.761905	3.2910	4.1
999	849-09-3807	A	Yangon	Member	Female	Fashion accessories	88.34	7	30.9190	649.30	2019-02-18	13:28	Cash	618.38	4.761905	30.9190	6.6

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Dash Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts